The purpose of the proposed project is to test previously observed empirical links between the physical availability of alcohol and alcohol consumption and problems using data from the county level. While current research suggests a link between the availability of alcohol, measured in terms of per capita outlet densities, and specific problem outcomes, these studies have been conducted almost exclusively at the level of states in the United States. The current study (beginning December 1, 1992 and ending November 30, 1997) will examine time-series cross- sectional data on the forms and distributions of alcohol availability over a 4- to 14-year period to determine the extent to which physical availability is related to these outcomes in the state of California. In this proposal, specific relationships between forms of alcohol availability (on- vs. off-premise), patterns of alcohol consumption, and alcohol problems (for example, drunk driving) are predicted from theoretical models of alcohol consumption and routine activities related to drinking. The connecting links between availability and problems are the forms of alcohol consumption and purchasing patterns to be expected in association with forms of retail alcohol sales. Routine activities related to the consumption of alcoholic beverages purchased at specific outlet types are directly related to the risk of involvement in specific alcohol problems. Two data acquisition and analysis strategies will be implemented during the project: (1) Up to 14 years or archival data will be used to establish the validity of predicted outlet-problem relations based on the routine activity model. Since a major component of the analysis of these relations involves measurement of contemporaneous spatiotemporal distributions of outlets and problems, these relations will be tested using time-series cross-sectional spatial models developed specifically for this purpose. (2) Four years of survey data on consumption patterns and routine activities related to alcohol use will be collected to further validate the predictions of the routine activity model in a time- series cross-sectional spatial panel.